Image computing is a term which consolidates the different disciplines that deal with images. Recent advances in very large scale integration (VLSI) technology, computer architectures, high resolution raster displays, and accurate image digitization devices have stimulated the demand for applications which require advanced image computing capabilities.
Image processing uses various aspects of optics, electronics, mathematics and computer techniques to transform an input image into another image that has desirable properties to the user. This is done by applying some type of transformation to the original image to produce a processed output image. In comparison, image analysis is the process that transforms a digital image into something other than a digital image, such as a set of measurements or objects, or a decision. Image analysis also includes the analysis of scenes or reconstruction of two- or three-dimensional objects from images or a set of projections. Thus, image analysis can be described as a transformation of information from an image space to some type of database for further analysis or processing. The term image processing is loosely used to cover both image processing and analysis.
While image processing is concerned with the analysis, enhancement, or reconstruction of images, the related field of graphics is concerned with synthesis of pictures of real or imaginary objects from a descriptive database. While image processing and graphics both deal with the computer processing of images, they have until recent years been quite separate disciplines.
Both graphics and image processing can be thought of as dealing with static images, which is often an excellent means of communicating information to a user. However, the dynamic variation of images to change the content, format, size, color or orientation is an even better means of communicating information to a user; the user is able to understand data, perceive trends, etc. Thus, interactive image computing, which allows human input to control the processing of images in real time, provides enhanced communication of information to the user. Images, graphics, text, data, and even audio information can be manipulated, integrated and presented by such a system.
An example of a prior art graphics system includes components for converting digital image data to analog display data. Components in such a system include a video frame buffer memory, a lookup table, and a digital-to-analog converter. A digital image is stored in the video frame buffer. Image data from the video frame buffer is input to the lookup table which converts the image data into display data in accordance with the color conversion scheme established in the table. The display data is transformed into an analog signal by the converter. The analog signal is used to drive a video display. Major considerations for such graphics systems are the diversity of color that is available and the number and size of images that can be readily displayed.
With respect to color image generation, a common color graphics system includes a red-green-blue (RGB) digital-to-analog converter (DAC) that has a built-in lookup table. The RGB-DAC generates red, green and blue analog signals on separate channels. The set of signals are used to drive a video display device. It is common to input 8-bits of digital image information into such a system. Thus, 256 (2.sup.8) different color output combinations can be selected by the input without changing the lookup table contents. When a single input looks up a set of red, green and blue outputs, the system is referred to as a pseudocolor system. Each output may be a different analog signal level. A special case of pseudocolor models is a grayscale model. For grayscale systems, the red, green and blue outputs are either the same analog signal or are separate outputs having the same level (value).
With the advent of VLSI and dense memory devices, it has become possible to have a graphics system that is capable of generating true color. In a conventional true color system, a series of three single channel-DACs are used. Each DAC is configured to output a single color--the red DAC outputs only red, the green DAC outputs only green, and the blue DAC outputs only blue. Separate components of image data for a single image are input to each DAC. For example, in one such system, 12-bits of input are used; three separate 4-bit image components generate each color, and a total of approximately 4,000 color entries can be selected. This mode can be compared to a 12-bit pseudocolor mode wherein a single input component selects from a set of 4,000 different red, green and blue outputs, but the input signal is not broken up into components that look up separate colors. In this example of a true color system, the single channel outputs from each DAC form a single RGB output set. In order for this system operate in a pseudocolor mode, the same image must be loaded into each DAC. This redundancy in the image frame buffer is not an efficient use of the frame buffer space. One of the drawbacks of such a system is that whether the true color system is operating in true color or pseudocolor mode, the frame buffer includes information related to a single image. The frame buffer includes either related components of a single image or repetitive data describing a single image. Multiple independent images cannot be simultaneously processed by the system.
An image processing system is characterized in part by the method in which it communicates with the main processor and by its processing capabilities measured in terms of speed, capacity, etc. Many image processing systems include one or more coprocessors, which may be connected to their own memory device.
Prior image computing systems have been developed around specialized processors such as the TMS34010 graphics system processor (GSP) and TMS32020 digital signal processor (DSP), both available from Texas Instruments of Dallas, Tex. Drawbacks in such a system include the limited 16-bit fixed-point arithmetic capability of the digital signal processor, which causes accuracy problems in some image processing and graphics operations due to overflow, truncation, etc. The communication between the graphics system processor and the digital signal processor, for example, using first-in first-out (FIFO) buffers, is inefficient and difficult to manage.
The graphics system in this particular example includes a display with a resolution of 512.times.512 pixels. Additionally, the graphics system includes two lookup tables, and an RGB-DAC using 12-bits of input. An overlay image selected from 128 colors can be displayed using one of the lookup tables. In this particular example, the overlay image is the same as the primary image but is displayed using a different color scheme. This graphics system has certain drawbacks. For example, a screen aspect ratio different than 1:1 (i.e., 512.times.512 displayed on a rectangular screen requires that images be warped in order for them to appear in proper proportion on the screen. Additionally, for many applications, 512.times.512 display resolution is inadequate. Finally, only one image is readily displayable at a time.
In an alternative system, the Texas Instruments 74ACT8837 floating-point processor (FPP) replaces the digital signal processor in the system above-described in order to provide high performance floating-point implementation of computationally-intensive image processing and graphics algorithms. However, the graphic capabilities of the system were not modified and did not advance with the processing capabilities.
Fields which rely increasingly on imaging computing techniques include medicine, military, industrial, and scientific applications. A prime example is the medical field. Current needs in the medical field include medical image enhancement, simple measurement or scientific visualization of change, movement, and flow, as well as successive 2-D slices and 3-D medical images. X-ray computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET) all use computationally intensive reconstruction methods to produce detailed cross sections of structures. Picture archiving and communications system (PACS) with filmless archiving for a set of images is a powerful concept with vast untapped potential. High performance image computing workstations are essential for continued development in these areas.